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Projects in chemo- and bioinformatics often consist of scattered data in various types and are difficult to access in a meaningful way for efficient data analysis. Data is usually too diverse to be even manipulated effectively. Sdfconf is data manipulation and analysis software to address this problem in a logical and robust manner. Other software commonly used for such tasks are either not designed with molecular and/or conformational data in mind or provide only a narrow set of tasks to be accomplished. Furthermore, many tools are only available within commercial software packages. Sdfconf is a flexible, robust, and free-of-charge tool for linking data from various sources for meaningful and efficient manipulation and analysis of molecule data sets. Sdfconf packages molecular structures and metadata into a complete ensemble, from which one can access both the whole data set and individual molecules and/or conformations. In this software note, we offer some practical examples of the utilization of sdfconf.

The estimation of the correct binding mode and affinity of a ligand into a target protein using computational methods is challenging. However, docking can introduce poses from which the correct binding mode could be identified using other methods. Here, we analyzed the reliability of binding energy estimation using the molecular mechanics-generalized Born surface area (MMGBSA) method without and with energy minimization to identify the likely ligand binding modes within docking results. MMGBSA workflow (a) outperformed docking in recognizing the correct binding modes of androgen receptor ligands and (b) improved the correlation coefficient of computational and experimental results of rescored docking poses to phosphodiesterase 4B. Combined with stability and atomic distance analysis, MMGBSA helped to (c) identify the binding modes and sites of metabolism of cytochrome P450 2A6 substrates. The standard deviation of estimated binding energy within one simulation was lowered by minimization in all three example cases. Minimization improved the identification of the correct binding modes of androgen receptor ligands. Although only three case studies are shown, the results are analogous and indicate that these behaviors could be generalized. Such identified binding modes could be further used, for example, with free energy perturbation methods to understand binding energetics more accurately.

A comprehensive set of 3-phenylcoumarin analogues with polar substituents was synthesised for blocking oestradiol synthesis by 17-b-hydroxysteroid dehydrogenase 1 (HSD1) in the latter part of the sulphatase pathway. Five analogues produced 62% HSD1 inhibition at 5 mM and, furthermore, three of them produced 68% inhibition at 1 mM. A docking-based structure-activity relationship analysis was done to determine the molecular basis of the inhibition and the cross-reactivity of the analogues was tested against oestrogen receptor, aromatase, cytochrome P450 1A2, and monoamine oxidases. Most of the analogues are only modestly active with 17-b-hydroxysteroid dehydrogenase 2 – a requirement for lowering effective oestradiol levels in vivo. Moreover, the analysis led to the synthesis and discovery of 3-imidazolecoumarin as a potent aromatase inhibitor. In short, coumarin core can be tailored with specific ring and polar moiety substitutions to block either the sulphatase pathway or the aromatase pathway for treating breast cancer and endometriosis. peerReviewed

Members of the Rab GTPase family are master regulators of vesicle trafficking. When disregulated, they are associated with a number of pathological states. The inhibition of RGGT, an enzyme responsible for post-translational geranylgeranylation of Rab GTPases represents one way to control the activity of these proteins. Because the number of molecules modulating RGGT is limited, we combined molecular modeling with biological assays to ascertain how modifications of phosphonocarboxylates, the first reported RGGT inhibitors, rationally improve understanding of their structure-activity relationship. We have identified the privileged position in the core scaffold of the imidazo[1,2-a]pyridine ring, which can be modified without compromising compounds' potency. Thus modified compounds are micromolar inhibitors of Rab11A prenylation, simultaneously being inactive against Rap1A/Rap1B modification, with the ability to inhibit proliferation of the HeLa cancer cell line. These findings were rationalized by molecular docking, which recognized interaction of phosphonic and carboxylic groups as decisive in phosphonocarboxylate localization in the RGGT binding site.

A novel virtual screening methodology called fragment- and negative image-based (F-NiB) screening is introduced and tested experimentally using phosphodiesterase 10A (PDE10A) as a case study. Potent PDE10A-specific small-molecule inhibitors are actively sought after for their antipsychotic and neuroprotective effects. The F-NiB combines features from both fragment-based drug discovery and negative image-based (NIB) screening methodologies to facilitate rational drug discovery. The selected structural parts of protein-bound ligand(s) are seamlessly combined with the negative image of the target's ligand-binding cavity. This cavity- and fragment-based hybrid model, namely its shape and electrostatics, is used directly in the rigid docking of ab initio generated ligand 3D conformers. In total, 14 compounds were acquired using the F-NiB methodology, 3D quantitative structure-activity relationship modeling, and pharmacophore modeling. Three of the small molecules inhibited PDE10A at ~27 to ~67 μM range in a radiometric assay. In a larger context, the study shows that the F-NiB provides a flexible way to incorporate small-molecule fragments into the drug discovery.

Intestinal and hepatic glucuronidation by the UDP-glucuronosyltransferases (UGTs) greatly affect the bioavailability of phenolic compounds. UGT1A10 catalyzes glucuronidation reactions in the intestine, but not in the liver. Here, our aim was to develop selective, fluorescent substrates to easily elucidate UGT1A10 function. To this end, homology models were constructed and used to design new substrates, and subsequently, six novel C3-substituted (4-fluorophenyl, 4-hydroxyphenyl, 4-methoxyphenyl, 4-(dimethylamino)phenyl, 4-methylphenyl, or triazole) 7-hydroxycoumarin derivatives were synthesized from inexpensive starting materials. All tested compounds could be glucuronidated to nonfluorescent glucuronides by UGT1A10, four of them highly selectively by this enzyme. A new UGT1A10 mutant, 1A10-H210M, was prepared on the basis of the newly constructed model. Glucuronidation kinetics of the new compounds, in both wild-type and mutant UGT1A10 enzymes, revealed variable effects of the mutation. All six new C3-substituted 7-hydroxycoumarins were glucuronidated faster by human intestine than by liver microsomes, supporting the results obtained with recombinant UGTs. The most selective 4(dimethylamino)phenyl and triazole C3-substituted 7-hydroxycoumarins could be very useful substrates in studying the function and expression of the human UGT1A10.

Identification of active ligands using computational methods is a challenging task. For example, molecular docking, pharmacophore modeling, and three dimensional quantitative structure-activity relationship models (3D-QSAR) are widely used methods to identify novel small molecules. However, all these methods have, in addition to advantages, also significant pitfalls. The aim of this study was to compare some commonly used computational methods to estimate their ability to separate highly active PDE4B-inhibitors from less active and inactive ones. Here, 152 molecules with pIC 50 -range of 3.4-10.5, originating from six original studies were used. High correlation coefficients by using docking, docking with postprocessing with molecular mechanics-generalized Born-surface area -method (MMGBSA), pharmacophore modeling, and 3D-QSAR were obtained. These results are well in line with earlier studies done with similar methods, and suggest that computational methods could be successfully used to identify novel PDE4B-inhibitors, especially if using multiple methods together.

Receiver operating characteristics (ROC) curve with the calculation of area under curve (AUC) is a useful tool to evaluate the performance of biomedical and chemoinformatics data. For example, in virtual drug screening ROC curves are very often used to visualize the efficiency of the used application to separate active ligands from inactive molecules. Unfortunately, most of the available tools for ROC analysis are implemented into commercially available software packages, or are plugins in statistical software, which are not always the easiest to use. Here, we present Rocker, a simple ROC curve visualization tool that can be used for the generation of publication quality images. Rocker also includes an automatic calculation of the AUC for the ROC curve and Boltzmann-enhanced discrimination of ROC (BEDROC). Furthermore, in virtual screening campaigns it is often important to understand the early enrichment of active ligand identification, for this Rocker offers automated calculation routine. To enable further development of Rocker, it is freely available (MIT-GPL license) for use and modifications from our web-site ( http://www.jyu.fi/rocker ).

Utilization of computer-aided molecular discovery methods in virtual screening (VS) is a cost-effective approach to identify novel bioactive small molecules. Unfortunately, no universal VS strategy can guarantee high hit rates for all biological targets, but each target requires distinct, fine-tuned solutions. Here, we have studied in retrospective manner the effectiveness and usefulness of common pharmacophore hypothesis, molecular docking and negative image-based screening as potential VS tools for a widely applied drug discovery target, estrogen receptor α (ERα). The comparison of the methods helps to demonstrate the differences in their ability to identify active molecules. For example, structure-based methods identified an already known active ligand from the widely-used bechmarking decoy molecule set. Although prospective VS against one commercially available database with around 100,000 drug-like molecules did not retrieve many testworthy hits, one novel hit molecule with pIC50 value of 6.6, was identified. Furthermore, our small in-house compound collection of easy-to-synthesize molecules was virtually screened against ERα, yielding to five hit candidates, which were found to be active in vitro having pIC50 values from 5.5 to 6.5. peerReviewed

Molecular docking is by far the most common method used in protein structure-based virtual screening. This paper presents Panther, a novel ultrafast multipurpose docking tool. In Panther, a simple shape-electrostatic model of the ligand-binding area of the protein is created by utilizing the protein crystal structure. The features of the possible ligands are then compared to the model by using a similarity search algorithm. On average, one ligand can be processed in a few minutes by using classical docking methods, whereas using Panther processing takes

Sticholysin II (StnII) is a pore-forming toxin from the sea anemone Stichodactyla heliantus which belongs to the large actinoporin family. The toxin binds to sphingomyelin (SM) containing membranes, and shows high binding specificity for this lipid. In this study, we have examined the role of the hydrogen bonding groups of the SM long-chain base (i.e., the 2NH and the 3OH) for StnII recognition. We prepared methylated SM-analogs which had reduced hydrogen bonding capability from 2NH and 3OH. Both surface plasmon resonance experiments, and isothermal titration calorimetry measurements indicated that StnII failed to bind to bilayers containing methylated SM-analogs, whereas clear binding was seen to SM-containing bilayers. StnII also failed to induce calcein release (i.e., pore formation) from vesicles made to contain methylated SM-analogs, but readily induced calcein release from SM-containing vesicles. Molecular modeling of SM docked to the phosphocholine binding site of StnII indicated that the 2NH and 3OH groups were likely to form a hydrogen bond with Tyr135. In addition, it appeared that Tyr111 and Tyr136 could donate hydrogen bonds to phosphate oxygen, thus stabilizing SM binding to the toxin. We conclude that the interfacial hydrogen bonding properties of SM, in addition to the phosphocholine head group, are crucial for high-affinity SM/StnII-interaction.

Reliable and effective virtual high-throughput screening (vHTS) methods are desperately needed to minimize the expenses involved in drug discovery projects. Here, we present an improvement to the negative image-based (NIB) screening: the shape, the electrostatics, and the solvation state of the target protein’s ligand-binding site are included into the vHTS. Additionally, the initial vHTS results are postprocessed with molecular mechanics/generalized Born surface area (MMGBSA) calculations to estimate the favorability of ligand-protein interactions. The results show that docking produces very good early enrichment for phosphodiesterase-5 (PDE-5); however, in general, the NIB and the ligand-based screening performed better with or without the added electrostatics. Furthermore, the postprocessing of the NIB screening results using MMGBSA calculations improved the early enrichment for the PDE-5 considerably, thus, making hit discovery affordable.

T-cell protein tyrosine phosphatase (TCPTP) is a ubiquitously expressed non-receptor protein tyrosine phosphatase. It is involved in the negative regulation of many cellular signaling pathways. Thus, activation of TCPTP could have important therapeutic applications in diseases such as cancer and inflammation. We have previously shown that the α-cytoplasmic tail of integrin α1β1 directly binds and activates TCPTP. In addition, we have identified in a large-scale high-throughput screen six small molecules that activate TCPTP. These small molecule activators include mitoxantrone and spermidine. In this study, we have investigated the molecular mechanism behind agonist-induced TCPTP activation. By combining several molecular modeling and biochemical techniques, we demonstrate that α1-peptide and mitoxantrone activate TCPTP via direct binding to the catalytic domain, whereas spermidine does not interact with the catalytic domain of TCPTP in vitro. Furthermore, we have identified a hydrophobic groove surrounded by negatively charged residues on the surface of TCPTP as a putative binding site for the α1-peptide and mitoxantrone. Importantly, these data have allowed us to identify a new molecule that binds to TCPTP, but interestingly cannot activate its phosphatase activity. Accordingly, we describe here mechanism of TCPTP activation by mitoxantrone, the cytoplasmic tail of α1-integrin, and a mitoxantrone-like molecule at the atomic level. These data provide invaluable insight into the development of novel TCPTP activators, and may facilitate the rational discovery of small-molecule cancer therapeutics.

The aim of this study was to examine how structural properties of different sphingomyelin (SM) analogs affected their substrate properties with sphingomyelinase (SMase) from Bacillus cereus. Using molecular docking and dynamics simulations (for SMase–SM complex), we then attempted to explain the relationship between SM structure and enzyme activity. With both micellar and monolayer substrates, 3O-methylated SM was found not to be degraded by the SMase. 2N-methylated SM was a substrate, but was degraded at about half the rate of its 2NH–SM control. PhytoPSM was readily hydrolyzed by the enzyme. PSM lacking one methyl in the phosphocholine head group was a good substrate, but PSM lacking two or three methyls failed to act as substrates for SMase. Based on literature data, and our docking and MD simulations, we conclude that the 3O-methylated PSM fails to interact with Mg2+ and Glu53 in the active site, thus preventing hydrolysis. Methylation of 2NH was not crucial for binding to the active site, but appeared to interfere with an induced fit activation of the SMase via interaction with Asp156. An OH on carbon 4 in the long-chain base of phytoPSM appeared not to interfere with the 3OH interacting with Mg2+ and Glu53 in the active site, and thus did not interfere with catalysis. Removing two or three methyls from the PSM head group apparently increased the positive charge on the terminal N significantly, which most likely led to ionic interactions with Glu250 and Glu155 adjacent to the active site. This likely interaction could have misaligned the SM substrate and hindered proper catalysis.